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Knowledge of past chmate variability is vital if the causes of observed chmate changes since instrumental records began are to be fully understood, particularly those, post-1850 AD, possibly due to anthropogenic activity. The past two millennia provide a long enough background with which to compare post-r850 AD change, whilst errors on proxy records remain relatively small. In the Eastem Mediterranean changes in water balance are of particular interest as water is an important resource. Oxygen isotope records from lakes in the region record changes in water balance and are therefore an important archive for observing natural, and anthropogenicaly forced, variabiUty in hydrology. Full understanding of cUmate proxies requires high-resolution analysis through the instramental time period for comparison with measured climate variability. Varved lake sediments provide the possibility for obtaining annually-resolvedarchives of climate proxies, andstrong chronological control through time. In this study gebchemical-climate proxies including oxygen and stable carbon isotope ratios were measured from two lakes in central Turkey with varved sediment archives. Lake Burdur's complex carbonate mineralogy and large catchment led to stable isotope data that is controlled by a variety of mischariisms and highlights the complex nature of some lake-isotope systems. A 1725 year long record was obtained from Nar GolU, with the top 900 years analysed at an annual resolution. Calibration of the top of this record with instmmental cHmate records suggests stable isotope variability at Nar is controlled by changes in evaporation, driven by changes in sunmier temperature and relative humidity. The proxy record from Nar shows sununer evaporation at Nar to be enhanced at times of increased Indian and African monsoon rainfall, and reduced during drier monsoon periods. Major shifts in the chmate system occur c. 500 and c. 1400 AD associated with times of change between relatively warm and cold periods of Northern Hemisphere temperatures. Cycles, with a frequency of 64 years, observed in the Nar isotope record and proxy records of solar activity suggest a solar forcing mechanism for decadal variability in the Eastem Mediterranean-Indian- African sununer climate system.

The Arctic sea-ice cover plays an important role for the global climate system. Sea ice and the overlying snow cover reflect up to eight times more of the solar radiation than the underlying ocean. Hence, they are important for the global energy budget, and changes in the sea-ice cover can have a large impact on the Arctic climate and beyond. In the past 36 years the ice cover reduced significantly. The largest decline is observed in September, with a rate of more than 12% per decade. The negative trend is accompanied by large inter-annual sea-ice variability: in September the sea-ice extent varies by up to 27% between years. The processes controlling the large variability are not well understood. In this thesis the atmospheric contribution to the inter-annual sea-ice variability is explored. The focus is specifically on the thermodynamical effects: processes that are associated with a temperature change of the ice cover and sea-ice melt. Atmospheric reanalysis data are used to identify key processes, while experiments with a state-of-the-art climate model are conducted to understand their relevance throughout different seasons. It is found that in years with a very low September sea-ice extent more heat and moisture is transported in spring into the area that shows the largest ice variability. The increased transport is often associated with similar atmospheric circulation patterns. Increased heat and moisture over the Arctic result in positive anomalies of water vapor and clouds. These alter the amount of downward radiation at the surface: positive cloud anomalies allow for more longwave radiation and less shortwave radiation. In spring, when the solar inclination is small, positive cloud anomalies result in an increased surface warming and an earlier seasonal melt onset. This reduces the ice cover early in the season and allows for an increased absorption of solar radiation by the surface during summer, which further accelerates the ice melt. The modeling experiments indicate that cloud anomalies of similar magnitude during other seasons than spring would likely not result in below-average September sea ice. Based on these results a simple statistical sea-ice prediction model is designed, that only takes into account the downward longwave radiation anomalies or variables associated with it. Predictive skills are similar to those of more complex models, emphasizing the importance of the spring atmosphere for the annual sea-ice evolution. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript.</p>

Land subsidence is a common phenomenon worldwide. When mitigation has approached a limitation, adaptation becomes an important strategy for sustainable development. Specially, climate variability and changes can make more serious impacts on coastal areas. This study focused on adaptation to land subsidence in Chiangyuan area consisting of several coastal villages, Pingtung county, Taiwan. Little research about the adaptations had been done in this area, except there was some studies for its awareness. Using a case study approach with questionnaires, in-depth interview, direct observation, this study explored past and existed adaptation behaviour in different categories of stakeholders. Moreover, we also tried to analyze the capacity of these adaptation for future impacts from land subsidence and flood made by climate change, and could increase the capacity. The results have revealed local people in Chiangyuan area had abundant experiences on adaptations to land subsidence and flood. They used different kinds of adaptation at same time to cope with flooding, land loss, and salted land problems. The followings have summarized the adaptation of four categories of stakeholders. 1. for local citizen, the major adaptation is house-elevating, who didn¡¦t adopt house elevating were without budget or planning to move out. 2. for farmer, planting economic fruits with higher tolerance to salt-water. 3. for aquaculture, fish-pond elevating, harvesting earlier, or building fish-pond on higher land. 4. for school, using water-proof gates or no classes during flooding. Some suggestion focused on adaptation to land subsidence was also given in this study, specially for government.

El Niño Southern Oscillation (ENSO) is the most important interannual mode of climate variability in the tropical Pacific affecting the globe through teleconnections. The evolution of ENSO is studied with focus on individual El Nino (EN) events; factors and processes explaining the behaviours of different EN flavours are identified. The comparison to model simulations reveals a number of biases that explain differences in model behaviour. Based on reanalysis data, ENs are divided into Central Pacific (CPEN), Eastern Pacific (EPEN), and Hybrid (HBEN). ENs are found to form a continuous spectrum of events with CPEN and EPEN as its end members depending on: (1) the Western Pacific subsurface potential temperature anomaly (PTA) about 1 year before the EN peak, and (2) the Western to Central Pacific cumulative zonal wind anomaly (ZWA) between the onset and peak of the EN. Using these two parameters, about 70% of the total variance of the maximum EN SSTA can be explained up to 6 months in advance. ZWA describes the potential for triggering Kelvin waves for a given initial West Pacific recharge state as captured by PTA. A cross-validated statistical model is developed to hindcast the 1980-2016 Nov-Dec-Jan (NDJ) mean Niño3.4 SSTA based on the two parameters. The model is comparable to, or even outperforms, many NOAA Climate Prediction Centre's statistical models during the boreal spring predictability barrier. The explained variance between observed and predicted NDJ Niño3.4 SSTA at a lead-time of 8 months is 57% using five years for cross-validation. Predictive skills are lower after 2000 when the mean climate state is more La Niña-like due to stronger equatorial easterly ZWA caused by an intensification of both, Walker and Hadley cell. The ability of climate models to simulate and predict EN is assessed with data from the Climate Model Inter-comparison Project 5 (CMIP5). Most models are able to capture the main features of different EN types. But models struggle to reproduce large intensity ENs as found in observations. This issue can be traced back to a failure to realistically simulate the oceanic recharged state and the subsequent Kelvin waves for intense EN. Causes of EN involve Kelvin waves that are triggered by westerly wind bursts (WWB). From higher temporal resolution of reanalysis data, WWBs above a certain threshold are required to trigger a Kelvin wave. Kelvin waves are triggered in locations of positive Ocean Heat Content (OHC) anomalies. Intensity, longitudinal coverage and duration of a WWB, the strength of the OHC anomaly and gradient influence the amplitude of Kelvin waves as they propagate. Synoptic pattern analysis suggests that most WWBs are caused by cyclones with the combination of an active Madden-Julian Oscillation. The NorESM is able to reproduce many characteristics of observed WWBs, OHC anomalies and their relation to Kelvin waves. However, differences are noticeable for the distribution of synoptic patterns causing WWBs in the model. In future work, climate models can be used to disentangle causes and effects of EN for correlations identified here with the ultimate goal to advance our understanding of ENSO, its variability and future changes.

As population and urbanization increase across the United States, the effects of natural hazards may well increase, as extreme events would increasingly affect concentrated populations and the infrastructure upon which they rely. Extreme precipitation is one natural hazard that could stress concentrated populations, and climate change research is engaging heavy precipitation frequency and its impacts. This research focuses on the less-studied phenomenon of an extreme precipitation reversal - defined as an unusually wet (dry) period that is preceded by an unusually dry (wet) period. The magnitude is expressed as the difference in the percentiles of the consecutive periods analyzed. This concept has been documented only once before in a study that analyzed extreme precipitation reversals for a region within the southwestern United States. That study found that large differences in precipitation from consecutive winters, a hydrologically critical season for the region, occurred more frequently than what would be expected from random chance, and that extreme precipitation reversals have increased significantly since 1960. This research expands upon the previous work by extending the analysis to the entire continental United States and by including multiple temporal resolutions. Climate division data were used to determine seasonal and annual precipitation for each of nine climate regions of the continental United States from 1895-2014. Precipitation values were then ranked and given percentiles for seasonal and annual data. The season-to-season analysis was performed in two ways. The first examined consecutive seasons (e.g., winter–spring, spring–summer) while the second analyzed the seasonal data from consecutive years (e.g., spring 2014–spring 2015). The annual data represented precipitation for the period October 1–September 30, or the 'water year' used by water resource managers. Following the approach of the previous study, a secondary objective of the research was to examine large-scale climate teleconnections for historical relationships with the occurrence of precipitation reversals. The El Nino-Southern Oscillation was chosen for analysis due to its well-known relationships with precipitation patterns across the United States. Results indicate regional expressions of a propensity for extreme precipitation reversals and relationships with teleconnections that may afford stakeholders guidance for proactive management. Precipitation reversal (PR) and extreme precipitation reversal (EPR) values were significantly larger for the second half of the study period for the western United States for the winter-to-winter, spring-to-spring, and year-to-year analyses. The fall-to-fall analysis also revealed changes in PR/EPR values for several regions, including the northwest, the Northern Rockies and Plains, and the Ohio Valley. Relationships between the winter-to-winter PR time series and an index representing the El Nino-Southern Oscillation (ENSO) phenomenon were examined. The winter-to-winter PR time series of the Northern Rockies and Plains region and the South exhibited significant relationships with the time series of Niño 3.4 values. El Niño (La Niña) coincided with more wet-to-dry (dry-to-wet) PR/EPR values for the Northern Rockies and Plains, while El Niño (La Niña) coincided with more dry-to-wet (wet-to-dry) PR/EPR values for the South. / Master of Science

Understanding the spatiotemporal pattern of near-surface ozone is the key part of polar atmospheric environment. The near-surface ozone can be depleted by the catalytic bromine chemistry in the heterogeneous phase but produced due to the snow photochemistry of nitrogen. In addition to the local chemistry, ozone pattern is also affected by regional meteorology and air-mass transport. Since the polar region is quite sensitive to the climate change, these conditions can be also affected by climate change and variability. Based on the analysis of large amount of dataset combined with in-situ observations, satellite measurements, model simulations, and global reanalysis data, the characteristics of polar ozone pattern and relation to the regional and large-scale atmospheric situations were investigated. At first, the characteristics of tropospheric ozone depletion events (ODEs) in the Arctic spring (April 2008) with satellite measured BrO and backtrajectories. Analysis of these data shows that the ODEs are due to either local halogen chemistry or short-range transport from adjacent high-BrO regions. Sometimes local ozone loss is surprisingly deep, particularly the unstable boundary layer at Churchill seems contribute to free-tropospheric BrO. Continually the influences of large-scale atmospheric patterns to the polar surface ozone are investigated. In years with frequent ODEs at Barrow and Alert, the WP teleconnection pattern is usually in its negative phase, during which the Pacific jet is strengthened but the storm track from western Pacific is weakened. Both factors tend to reduce the transport of ozone-rich airmass from mid-latitudes to the Arctic, creating a favorable environment for the Arctic ODEs. Comparison between Barrow and Alert shows the initiation of ODEs in spring is decided by the solar intensity and the termination is by the surface air temperature. Monthly frequency of ODEs also indicate the wind strength from the Arctic Ocean is largely influential to ODEs. The surface ozone at South Pole reveals year-round reversal trends during 3 decades, which is consistent with what lower-tropospheric temperature shows. Their strong correlation implies the possibility of large meridional mixing in warm conditions, which enhances the background level of ozone and nitrogen at South Pole.

Economic research on climate and productivity effects of ocean phenomena has mostly focused on interannual cases such as the El Niño Southern Oscillation. Here Decadal climate variability (DCV) refers to ocean related climate influences of duration from seven to twenty years. The specific phenomena analyzed here are the Pacific Decadal Oscillation, the Tropical Atlantic Gradient and the West Pacific Warm Pool. Their positive and negative phases, occurring individually or in combination, are associated with variations in crop and water yields. This dissertation examines the value of DCV information to agriculture and water users in the Missouri river basin using a price endogenous agricultural and non-agricultural model that depicts cropping and water use. The model is used to evaluate the welfare gains and adaptations given various levels of DCV information. The analysis shows the value (for a 10-year average) for a perfect forecast is about 5.2 billion dollars, though 86% of this value, 4.55 billion dollars, can be obtained by a less perfect forecast based on already available data in the form of the prediction of DCV phase under transition probabilities. The results indicate that forecasting any DCV state is important because of differential responses in the acreage of major crops plus water use adjustments by residential, agricultural and industrial users.

The first part of this thesis is an assessment of the ability of global climate models to reproduce observed features of the leading Empirical Orthogonal Function (EOF) mode of North Pacific sea surface temperature (SST) anomalies known as the Pacific Decadal Oscillation (PDO). The simulations from 13 global climate models I am analyzing were performed under phase 3 of the coupled model intercomparison project (CMIP3). In particular, I am investigating whether these climate models capture tropical influences on the PDO, and the influences of the PDO on North American surface temperature and precipitation. My results are that 1) the models as group produce a realistic pattern of the PDO. The simulated variance of the PDO index is overestimated by roughly 30%. 2) The tropical influence on North Pacific SSTs is biased systematically in these models. The simulated response to El Niño-Southern Oscillation (ENSO) forcing is delayed compared to the observed response. This tendency is consistent with model biases toward deeper oceanic mixed layers in winter and spring and weaker air-sea feedbacks in the winter half-year. Model biases in mixed layer depths and air-sea feedbacks are also associated with a model mean ENSO-related signal in the North Pacific whose amplitude is overestimated by roughly 30%. Finally, model power spectra of the PDO signal and its ENSO-forced component are “redder” than observed due to errors originating in the tropics and extratropics. 3) The models are quite successful at capturing the influence of both the tropical Pacific related and the extratropical part of the PDO on North American surface temperature. 4) The models capture some of the influence of the PDO on North American precipitation mainly due to its tropical Pacific related part. In the second part of this thesis, I investigate the ability of one such coupled ocean- atmosphere climate model, carefully initialized with observations, to dynamically predict the future evolution of the PDO on seasonal to decadal time scales. I am using forecasts produced by the Canadian climate data assimilation and prediction system employing the Canadian climate model CanCM3 for seasonal (CHFP2) and CanCM4 for decadal (DHFP1) predictions. The skill of this system in predicting the future evolution of the PDO index is then inferred from a set of historical “forecasts” called hindcasts. In this manner, hindcasts are issued over the past 30 years (seasonal), or over the past 50 years (decadal) when they can be verified against the observed historical evolution of the PDO index. I find that 1) CHFP2 is successful at predicting the PDO at the seasonal time scale measured by mean-square skill score and correlation skill. Weather “noise” unpredictable at the seasonal time scale generated by substantial North Pacific storm track activity that coincides with a shallow oceanic mixed layer in May and June appear to pose a prediction barrier for the PDO. PDO skill therefore depends on the start season of the forecast. PDO skill also varies as a function of the target month. Variations in North Pacific storminess appear to impact PDO skill by means of a lagged response of the ocean mixed layer to weather “noise”. In CHFP2, times of increasing North Pacific storm track activity are followed by times of reduced PDO skill, while the North Pacific midwinter suppression of storm track activity with decreasing storminess is followed by a substantial recovery in PDO skill. 2) This system is capable of forecasting the leading 14 EOF modes of North Pacific SST departures, that explain roughly three quarters of the total SST variance. CHFP2 is less successful at predicting North Pacific SSTs, i.e., the combination of all the EOF modes, at the seasonal time scale. 3) Besides the skill in Pacific SST, CHFP2 skillfully predicts indices that measure the atmospheric circulation regime over the North Pacific and North America such as the Pacific/North American pattern (PNA) (skillful for three out of four start seasons) and the North Pacific index (NPI) (skillful for all four start seasons). 4) CHFP2 is successful at forecasting part of the influence of Pacific SST on North American climate at the seasonal time scale. Measured by 12-month average anomaly correlation skill, in this system the PDO is a better predictor for North American precipitation (skillful for all four start seasons) than temperature (skillful for one out of four start seasons). In CHFP2, ENSO is a better predictor for North American temperature (skillful for all four start seasons) than the PDO. Both ENSO and the PDO are, however, good predictors for North American precipitation (skillful for all four start seasons). Finally, DHFP1 is less successful at forecasting the PDO at the decadal time scale. Ten-year forecasts of the PDO index exhibit significantly positive correlation skill exclusively in the first year of the forecast. When the correlation skill of the predicted index averaged over lead years is considered, the PDO skill in this system stays significantly positive during the first three years of the decadal forecast. In other words, this climate data assimilation and prediction system is expected to skillfully predict the future three year averaged evolution of the PDO index, but not the evolution of the index in each year individually. / Graduate

The upper Colorado River basin (UCRB) is one of the primary sources of water for the western United States, and increasing temperatures likely will elevate the risk of reduced water supply in the basin. Although variability in water-year precipitation explains more of the variability in water-year UCRB streamflow than water-year UCRB temperature, since the late 1980s, increases in temperature in the UCRB have caused a substantial reduction in UCRB runoff efficiency (the ratio of streamflow to precipitation). These reductions in flow because of increasing temperatures are the largest documented temperature-related reductions since record keeping began. Increases in UCRB temperature over the past three decades have resulted in a mean UCRB water-year streamflow departure of 21306 million m(3) (or -7% of mean water-year streamflow). Additionally, warm-season (April through September) temperature has had a larger effect on variability in water-year UCRB streamflow than the cool-season (October through March) temperature. The greater contribution of warm-season temperature, relative to cool-season temperature, to variability of UCRB flow suggests that evaporation or snowmelt, rather than changes from snow to rain during the cool season, has driven recent reductions in UCRB flow. It is expected that as warming continues, the negative effects of temperature on water-year UCRB streamflow will become more evident and problematic.